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5.2 Evaluation Results and Leaderboards

This generated report is the complete static comparison of the committed evaluation and judgment snapshots. It complements the evaluation methodology, the narrative comparison, the dataset complexity ladder, and the raw result snapshots.

Model provenance. Recorded judge models: gemma4:31b, qwen3.6:latest. Recorded Ragas evaluator models: mistral-small3.2:24b. Active plugin generation role models: qwen3.8:latest. Active LightRAG role models: qwen3.8:latest. Snapshot model names remain unchanged because they identify the systems that produced the recorded answers and scores.

1. Reading the Results

The default overall order is the dataset-macro judge mean: each measured dataset contributes one equally weighted judge mean. Query-weighted judge mean is shown separately and weights each evaluated query equally. No composite score combines quality, coverage, latency, or operational reliability.

Higher judge, answer-relevancy, faithfulness, eligible-coverage, successful-response, and per-query-win values are better. Lower ranks, disagreement, latency, error rate, errors, and timeouts are better. Judge coverage is evaluated judge questions over all judge questions. Ragas coverage is evaluated rows over eligible rows (total rows - ineligible), while each metric's total rows, ineligible rows, evaluator errors, and timeouts remain separate columns. N/A means no value was recorded or no rows were eligible and carries an empty machine sort value. Faithfulness ineligible rows are not failures and are never coerced to zero. Ragas evaluator errors and timeouts also remain separate from response errors and timeouts.

Base approaches and flavor aliases are intentionally separate tiers. A flavor identifies its base family but cannot occupy a base-approach rank.

2. Overall Base-Approach Leaderboard

Overall base-approach leaderboard
Overall judge rank Approach Maturity Dataset-macro judge Query-weighted judge Judge coverage Judge errors Judge gemma4:31b Judge gemma4:31b coverage Judge qwen3.6:latest Judge qwen3.6:latest coverage Judge disagreement Judge disagreement comparisons Mean dataset rank Best dataset rank Worst dataset rank Per-query wins Answer relevancy mean Answer relevancy coverage (eligible) Answer relevancy total rows Answer relevancy ineligible Answer relevancy errors Answer relevancy timeouts Faithfulness mean Faithfulness coverage (eligible) Faithfulness total rows Faithfulness ineligible Faithfulness errors Faithfulness timeouts Mean latency (ms) Successful Attempted Error rate Errors Timeouts
1 contextual-rag canonical 3.757 3.800 20 / 20 (100.00%) 0 3.550 20 / 20 (100.00%) 4.050 20 / 20 (100.00%) 0.600 20 2.000 1 3 4 0.872 20 / 20 (100.00%) 20 0 0 0 0.417 12 / 20 (60.00%) 20 0 8 0 17143.75 20 20 0.00% 0 0
2 lazy-graph-rag experimental 3.743 3.800 20 / 20 (100.00%) 0 3.650 20 / 20 (100.00%) 3.950 20 / 20 (100.00%) 0.500 20 2.000 1 3 4 0.851 20 / 20 (100.00%) 20 0 0 0 0.433 13 / 20 (65.00%) 20 0 7 0 6065.35 20 20 0.00% 0 0
2 vanilla-rag canonical 3.743 3.775 20 / 20 (100.00%) 0 3.650 20 / 20 (100.00%) 3.900 20 / 20 (100.00%) 0.850 20 2.000 1 3 4 0.798 20 / 20 (100.00%) 20 0 0 0 0.399 14 / 20 (70.00%) 20 0 6 0 5637.90 20 20 0.00% 0 0
4 hybrid-rag canonical 3.514 3.525 20 / 20 (100.00%) 0 3.500 20 / 20 (100.00%) 3.550 20 / 20 (100.00%) 0.750 20 4.000 2 6 4 0.868 20 / 20 (100.00%) 20 0 0 0 0.379 15 / 20 (75.00%) 20 0 5 0 16044.75 20 20 0.00% 0 0
5 graph-rag canonical 2.931 2.900 20 / 20 (100.00%) 0 2.600 20 / 20 (100.00%) 3.200 20 / 20 (100.00%) 0.900 20 5.667 5 7 4 0.805 20 / 20 (100.00%) 20 0 0 0 N/A N/A 20 20 0 0 15134.00 20 20 0.00% 0 0
6 n8n-adaptive-rag canonical 2.924 2.875 20 / 20 (100.00%) 0 2.750 20 / 20 (100.00%) 3.000 20 / 20 (100.00%) 0.850 20 4.667 2 6 0 0.779 20 / 20 (100.00%) 20 0 0 0 0.388 9 / 20 (45.00%) 20 0 11 0 6279.25 20 20 0.00% 0 0
7 agentic-rag canonical 2.701 2.675 20 / 20 (100.00%) 0 2.550 20 / 20 (100.00%) 2.800 20 / 20 (100.00%) 0.850 20 5.000 2 7 0 0.729 20 / 20 (100.00%) 20 0 0 0 0.443 9 / 20 (45.00%) 20 0 11 0 27434.60 20 20 0.00% 0 0

3. Base Approaches by Dataset

Base approaches by measured dataset
Dataset Complexity Approach Maturity Judge rank Judge mean Judge coverage Judge errors Judge gemma4:31b Judge gemma4:31b coverage Judge qwen3.6:latest Judge qwen3.6:latest coverage Judge disagreement Judge disagreement comparisons Per-query wins Answer relevancy rank Answer relevancy mean Answer relevancy coverage (eligible) Answer relevancy total rows Answer relevancy ineligible Answer relevancy errors Answer relevancy timeouts Faithfulness rank Faithfulness mean Faithfulness coverage (eligible) Faithfulness total rows Faithfulness ineligible Faithfulness errors Faithfulness timeouts Latency rank Mean latency (ms) Successful Attempted Error rate Errors Timeouts
baseline_curated 1 vanilla-rag canonical 1 4.167 6 / 6 (100.00%) 0 4.333 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 1.000 6 0 6 0.708 6 / 6 (100.00%) 6 0 0 0 1 0.672 6 / 6 (100.00%) 6 0 0 0 2 3833.83 6 6 0.00% 0 0
baseline_curated 1 hybrid-rag canonical 2 4.000 6 / 6 (100.00%) 0 4.333 6 / 6 (100.00%) 3.667 6 / 6 (100.00%) 1.000 6 1 2 0.869 6 / 6 (100.00%) 6 0 0 0 3 0.645 6 / 6 (100.00%) 6 0 0 0 6 17682.83 6 6 0.00% 0 0
baseline_curated 1 contextual-rag canonical 3 3.917 6 / 6 (100.00%) 0 3.500 6 / 6 (100.00%) 4.333 6 / 6 (100.00%) 0.833 6 0 1 0.894 6 / 6 (100.00%) 6 0 0 0 6 0.300 5 / 6 (83.33%) 6 0 1 0 7 18016.33 6 6 0.00% 0 0
baseline_curated 1 lazy-graph-rag experimental 3 3.917 6 / 6 (100.00%) 0 3.833 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 0.167 6 1 3 0.858 6 / 6 (100.00%) 6 0 0 0 4 0.636 5 / 6 (83.33%) 6 0 1 0 3 5514.00 6 6 0.00% 0 0
baseline_curated 1 graph-rag canonical 5 3.750 6 / 6 (100.00%) 0 3.667 6 / 6 (100.00%) 3.833 6 / 6 (100.00%) 0.500 6 4 4 0.842 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 5 12611.83 6 6 0.00% 0 0
baseline_curated 1 n8n-adaptive-rag canonical 6 3.333 6 / 6 (100.00%) 0 3.667 6 / 6 (100.00%) 3.000 6 / 6 (100.00%) 0.667 6 0 5 0.733 6 / 6 (100.00%) 6 0 0 0 5 0.564 5 / 6 (83.33%) 6 0 1 0 1 2798.33 6 6 0.00% 0 0
baseline_curated 1 agentic-rag canonical 7 2.667 6 / 6 (100.00%) 0 3.000 6 / 6 (100.00%) 2.333 6 / 6 (100.00%) 0.667 6 0 7 0.567 6 / 6 (100.00%) 6 0 0 0 2 0.664 5 / 6 (83.33%) 6 0 1 0 4 10773.67 6 6 0.00% 0 0
graph_native 2 lazy-graph-rag experimental 1 4.312 8 / 8 (100.00%) 0 4.125 8 / 8 (100.00%) 4.500 8 / 8 (100.00%) 0.625 8 2 4 0.829 8 / 8 (100.00%) 8 0 0 0 2 0.416 5 / 8 (62.50%) 8 0 3 0 2 4935.75 8 8 0.00% 0 0
graph_native 2 contextual-rag canonical 2 4.188 8 / 8 (100.00%) 0 4.000 8 / 8 (100.00%) 4.375 8 / 8 (100.00%) 0.625 8 2 3 0.841 8 / 8 (100.00%) 8 0 0 0 1 0.607 5 / 8 (62.50%) 8 0 3 0 5 11196.88 8 8 0.00% 0 0
graph_native 2 vanilla-rag canonical 3 4.062 8 / 8 (100.00%) 0 3.750 8 / 8 (100.00%) 4.375 8 / 8 (100.00%) 0.875 8 3 2 0.851 8 / 8 (100.00%) 8 0 0 0 4 0.279 5 / 8 (62.50%) 8 0 3 0 1 4539.25 8 8 0.00% 0 0
graph_native 2 hybrid-rag canonical 4 3.625 8 / 8 (100.00%) 0 3.375 8 / 8 (100.00%) 3.875 8 / 8 (100.00%) 0.750 8 1 1 0.859 8 / 8 (100.00%) 8 0 0 0 3 0.303 6 / 8 (75.00%) 8 0 2 0 4 9808.88 8 8 0.00% 0 0
graph_native 2 graph-rag canonical 5 2.625 8 / 8 (100.00%) 0 2.125 8 / 8 (100.00%) 3.125 8 / 8 (100.00%) 1.250 8 0 5 0.796 8 / 8 (100.00%) 8 0 0 0 N/A N/A N/A 8 8 0 0 6 12473.88 8 8 0.00% 0 0
graph_native 2 agentic-rag canonical 6 2.438 8 / 8 (100.00%) 0 2.125 8 / 8 (100.00%) 2.750 8 / 8 (100.00%) 0.625 8 0 6 0.740 8 / 8 (100.00%) 8 0 0 0 5 0.000 1 / 8 (12.50%) 8 0 7 0 7 29112.75 8 8 0.00% 0 0
graph_native 2 n8n-adaptive-rag canonical 6 2.438 8 / 8 (100.00%) 0 2.125 8 / 8 (100.00%) 2.750 8 / 8 (100.00%) 0.625 8 0 6 0.740 8 / 8 (100.00%) 8 0 0 0 5 0.000 1 / 8 (12.50%) 8 0 7 0 3 5299.00 8 8 0.00% 0 0
cyber_threat_intel 7 contextual-rag canonical 1 3.167 6 / 6 (100.00%) 0 3.000 6 / 6 (100.00%) 3.333 6 / 6 (100.00%) 0.333 6 2 1 0.891 6 / 6 (100.00%) 6 0 0 0 1 0.232 2 / 6 (33.33%) 6 0 4 0 6 24200.33 6 6 0.00% 0 0
cyber_threat_intel 7 agentic-rag canonical 2 3.000 6 / 6 (100.00%) 0 2.667 6 / 6 (100.00%) 3.333 6 / 6 (100.00%) 1.333 6 0 3 0.877 6 / 6 (100.00%) 6 0 0 0 2 0.224 3 / 6 (50.00%) 6 0 3 0 7 41858.00 6 6 0.00% 0 0
cyber_threat_intel 7 lazy-graph-rag experimental 2 3.000 6 / 6 (100.00%) 0 2.833 6 / 6 (100.00%) 3.167 6 / 6 (100.00%) 0.667 6 1 5 0.873 6 / 6 (100.00%) 6 0 0 0 4 0.121 3 / 6 (50.00%) 6 0 3 0 1 8122.83 6 6 0.00% 0 0
cyber_threat_intel 7 n8n-adaptive-rag canonical 2 3.000 6 / 6 (100.00%) 0 2.667 6 / 6 (100.00%) 3.333 6 / 6 (100.00%) 1.333 6 0 3 0.877 6 / 6 (100.00%) 6 0 0 0 2 0.224 3 / 6 (50.00%) 6 0 3 0 3 11067.17 6 6 0.00% 0 0
cyber_threat_intel 7 vanilla-rag canonical 2 3.000 6 / 6 (100.00%) 0 2.833 6 / 6 (100.00%) 3.167 6 / 6 (100.00%) 0.667 6 1 6 0.819 6 / 6 (100.00%) 6 0 0 0 5 0.052 3 / 6 (50.00%) 6 0 3 0 2 8906.83 6 6 0.00% 0 0
cyber_threat_intel 7 hybrid-rag canonical 6 2.917 6 / 6 (100.00%) 0 2.833 6 / 6 (100.00%) 3.000 6 / 6 (100.00%) 0.500 6 2 2 0.878 6 / 6 (100.00%) 6 0 0 0 6 0.000 3 / 6 (50.00%) 6 0 3 0 5 22721.17 6 6 0.00% 0 0
cyber_threat_intel 7 graph-rag canonical 7 2.417 6 / 6 (100.00%) 0 2.167 6 / 6 (100.00%) 2.667 6 / 6 (100.00%) 0.833 6 0 7 0.780 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 4 21203.00 6 6 0.00% 0 0

4. Overall Flavor-Alias Leaderboard

Overall flavor-alias leaderboard
Overall judge rank Flavor Base family Maturity Dataset-macro judge Query-weighted judge Judge coverage Judge errors Judge gemma4:31b Judge gemma4:31b coverage Judge qwen3.6:latest Judge qwen3.6:latest coverage Judge disagreement Judge disagreement comparisons Mean dataset rank Best dataset rank Worst dataset rank Per-query wins Answer relevancy mean Answer relevancy coverage (eligible) Answer relevancy total rows Answer relevancy ineligible Answer relevancy errors Answer relevancy timeouts Faithfulness mean Faithfulness coverage (eligible) Faithfulness total rows Faithfulness ineligible Faithfulness errors Faithfulness timeouts Mean latency (ms) Successful Attempted Error rate Errors Timeouts
1 hybrid-rag-fast hybrid-rag canonical 3.792 3.775 20 / 20 (100.00%) 0 3.600 20 / 20 (100.00%) 3.950 20 / 20 (100.00%) 0.650 20 2.667 1 5 2 0.797 20 / 20 (100.00%) 20 0 0 0 0.389 16 / 20 (80.00%) 20 0 4 0 4815.90 20 20 0.00% 0 0
2 hybrid-rag-high-recall hybrid-rag canonical 3.757 3.800 20 / 20 (100.00%) 0 3.500 20 / 20 (100.00%) 4.100 20 / 20 (100.00%) 0.600 20 3.667 1 7 2 0.877 20 / 20 (100.00%) 20 0 0 0 0.420 12 / 20 (60.00%) 20 0 8 0 23866.35 20 20 0.00% 0 0
3 lazy-graph-rag-wide lazy-graph-rag experimental 3.729 3.725 20 / 20 (100.00%) 0 3.650 20 / 20 (100.00%) 3.800 20 / 20 (100.00%) 0.450 20 3.667 1 7 2 0.818 20 / 20 (100.00%) 20 0 0 0 0.468 11 / 20 (55.00%) 20 0 9 0 7197.30 20 20 0.00% 0 0
4 vanilla-rag-wide vanilla-rag canonical 3.694 3.725 20 / 20 (100.00%) 0 3.400 20 / 20 (100.00%) 4.050 20 / 20 (100.00%) 0.750 20 3.000 2 5 4 0.839 20 / 20 (100.00%) 20 0 0 0 0.455 15 / 20 (75.00%) 20 0 5 0 8154.35 20 20 0.00% 0 0
5 contextual-rag-high-recall contextual-rag canonical 3.597 3.575 20 / 20 (100.00%) 0 3.400 20 / 20 (100.00%) 3.750 20 / 20 (100.00%) 0.450 20 4.333 2 7 0 0.855 20 / 20 (100.00%) 20 0 0 0 0.378 12 / 20 (60.00%) 20 0 8 0 24930.25 20 20 0.00% 0 0
5 lazy-graph-rag-fast lazy-graph-rag experimental 3.597 3.600 20 / 20 (100.00%) 0 3.300 20 / 20 (100.00%) 3.900 20 / 20 (100.00%) 0.700 20 4.333 3 5 3 0.846 20 / 20 (100.00%) 20 0 0 0 0.424 14 / 20 (70.00%) 20 0 6 0 4786.25 20 20 0.00% 0 0
7 lazy-graph-rag-balanced lazy-graph-rag experimental 3.479 3.500 20 / 20 (100.00%) 0 3.200 20 / 20 (100.00%) 3.800 20 / 20 (100.00%) 0.600 20 5.000 3 7 1 0.854 20 / 20 (100.00%) 20 0 0 0 0.465 13 / 20 (65.00%) 20 0 7 0 5752.70 20 20 0.00% 0 0
8 graph-rag-wide graph-rag canonical 2.875 2.850 20 / 20 (100.00%) 0 2.650 20 / 20 (100.00%) 3.050 20 / 20 (100.00%) 0.500 20 8.000 5 11 4 0.835 20 / 20 (100.00%) 20 0 0 0 N/A N/A 20 20 0 0 18603.75 20 20 0.00% 0 0
9 graph-rag-rerank graph-rag canonical 2.840 2.800 20 / 20 (100.00%) 0 2.700 20 / 20 (100.00%) 2.900 20 / 20 (100.00%) 0.400 20 9.000 9 9 1 0.822 20 / 20 (100.00%) 20 0 0 0 N/A N/A 20 20 0 0 21719.25 20 20 0.00% 0 0
10 n8n-adaptive-rag-default n8n-adaptive-rag canonical 2.708 2.675 20 / 20 (100.00%) 0 2.450 20 / 20 (100.00%) 2.900 20 / 20 (100.00%) 0.450 20 9.667 8 11 1 0.738 20 / 20 (100.00%) 20 0 0 0 0.463 9 / 20 (45.00%) 20 0 11 0 8158.95 20 20 0.00% 0 0
11 graph-rag-fast graph-rag canonical 2.549 2.500 20 / 20 (100.00%) 0 2.300 20 / 20 (100.00%) 2.700 20 / 20 (100.00%) 0.500 20 11.000 9 12 0 0.834 20 / 20 (100.00%) 20 0 0 0 N/A N/A 20 20 0 0 12400.35 20 20 0.00% 0 0
12 agentic-rag-deeper agentic-rag canonical 2.528 2.500 20 / 20 (100.00%) 0 2.350 20 / 20 (100.00%) 2.650 20 / 20 (100.00%) 0.400 20 10.667 9 12 0 0.725 20 / 20 (100.00%) 20 0 0 0 0.731 8 / 20 (40.00%) 20 0 12 0 17397.75 20 20 0.00% 0 0

5. Flavor Aliases by Dataset

Flavor aliases by measured dataset
Dataset Complexity Flavor Base family Maturity Judge rank Judge mean Judge coverage Judge errors Judge gemma4:31b Judge gemma4:31b coverage Judge qwen3.6:latest Judge qwen3.6:latest coverage Judge disagreement Judge disagreement comparisons Per-query wins Answer relevancy rank Answer relevancy mean Answer relevancy coverage (eligible) Answer relevancy total rows Answer relevancy ineligible Answer relevancy errors Answer relevancy timeouts Faithfulness rank Faithfulness mean Faithfulness coverage (eligible) Faithfulness total rows Faithfulness ineligible Faithfulness errors Faithfulness timeouts Latency rank Mean latency (ms) Successful Attempted Error rate Errors Timeouts
baseline_curated 1 lazy-graph-rag-wide lazy-graph-rag experimental 1 4.583 6 / 6 (100.00%) 0 4.500 6 / 6 (100.00%) 4.667 6 / 6 (100.00%) 0.167 6 1 9 0.798 6 / 6 (100.00%) 6 0 0 0 4 0.682 4 / 6 (66.67%) 6 0 2 0 5 6311.33 6 6 0.00% 0 0
baseline_curated 1 hybrid-rag-fast hybrid-rag canonical 2 4.083 6 / 6 (100.00%) 0 3.833 6 / 6 (100.00%) 4.333 6 / 6 (100.00%) 0.500 6 0 10 0.675 6 / 6 (100.00%) 6 0 0 0 6 0.626 6 / 6 (100.00%) 6 0 0 0 1 3227.83 6 6 0.00% 0 0
baseline_curated 1 vanilla-rag-wide vanilla-rag canonical 2 4.083 6 / 6 (100.00%) 0 3.833 6 / 6 (100.00%) 4.333 6 / 6 (100.00%) 0.500 6 0 6 0.846 6 / 6 (100.00%) 6 0 0 0 7 0.620 6 / 6 (100.00%) 6 0 0 0 4 5685.00 6 6 0.00% 0 0
baseline_curated 1 contextual-rag-high-recall contextual-rag canonical 4 3.917 6 / 6 (100.00%) 0 3.833 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 0.167 6 0 1 0.905 6 / 6 (100.00%) 6 0 0 0 9 0.200 5 / 6 (83.33%) 6 0 1 0 12 26844.50 6 6 0.00% 0 0
baseline_curated 1 graph-rag-wide graph-rag canonical 5 3.833 6 / 6 (100.00%) 0 3.667 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 0.333 6 3 8 0.833 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 8 17524.17 6 6 0.00% 0 0
baseline_curated 1 lazy-graph-rag-fast lazy-graph-rag experimental 5 3.833 6 / 6 (100.00%) 0 3.667 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 0.333 6 1 3 0.882 6 / 6 (100.00%) 6 0 0 0 8 0.595 6 / 6 (100.00%) 6 0 0 0 2 3392.67 6 6 0.00% 0 0
baseline_curated 1 hybrid-rag-high-recall hybrid-rag canonical 7 3.750 6 / 6 (100.00%) 0 3.500 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 0.500 6 0 2 0.893 6 / 6 (100.00%) 6 0 0 0 5 0.681 5 / 6 (83.33%) 6 0 1 0 11 26029.67 6 6 0.00% 0 0
baseline_curated 1 lazy-graph-rag-balanced lazy-graph-rag experimental 7 3.750 6 / 6 (100.00%) 0 3.500 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 0.500 6 0 4 0.868 6 / 6 (100.00%) 6 0 0 0 2 0.720 5 / 6 (83.33%) 6 0 1 0 3 4911.50 6 6 0.00% 0 0
baseline_curated 1 graph-rag-fast graph-rag canonical 9 3.667 6 / 6 (100.00%) 0 3.500 6 / 6 (100.00%) 3.833 6 / 6 (100.00%) 0.333 6 0 7 0.844 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 7 8759.67 6 6 0.00% 0 0
baseline_curated 1 graph-rag-rerank graph-rag canonical 9 3.667 6 / 6 (100.00%) 0 3.667 6 / 6 (100.00%) 3.667 6 / 6 (100.00%) 0.333 6 0 5 0.847 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 9 20866.33 6 6 0.00% 0 0
baseline_curated 1 n8n-adaptive-rag-default n8n-adaptive-rag canonical 11 3.167 6 / 6 (100.00%) 0 3.167 6 / 6 (100.00%) 3.167 6 / 6 (100.00%) 0.000 6 1 11 0.596 6 / 6 (100.00%) 6 0 0 0 3 0.700 5 / 6 (83.33%) 6 0 1 0 6 8537.00 6 6 0.00% 0 0
baseline_curated 1 agentic-rag-deeper agentic-rag canonical 12 2.917 6 / 6 (100.00%) 0 2.833 6 / 6 (100.00%) 3.000 6 / 6 (100.00%) 0.167 6 0 12 0.576 6 / 6 (100.00%) 6 0 0 0 1 1.000 4 / 6 (66.67%) 6 0 2 0 10 22713.50 6 6 0.00% 0 0
graph_native 2 hybrid-rag-high-recall hybrid-rag canonical 1 4.188 8 / 8 (100.00%) 0 3.875 8 / 8 (100.00%) 4.500 8 / 8 (100.00%) 0.625 8 1 1 0.855 8 / 8 (100.00%) 8 0 0 0 7 0.327 5 / 8 (62.50%) 8 0 3 0 7 10226.75 8 8 0.00% 0 0
graph_native 2 vanilla-rag-wide vanilla-rag canonical 2 4.000 8 / 8 (100.00%) 0 3.750 8 / 8 (100.00%) 4.250 8 / 8 (100.00%) 0.750 8 3 5 0.849 8 / 8 (100.00%) 8 0 0 0 2 0.488 6 / 8 (75.00%) 8 0 2 0 6 6094.25 8 8 0.00% 0 0
graph_native 2 lazy-graph-rag-balanced lazy-graph-rag experimental 3 3.688 8 / 8 (100.00%) 0 3.375 8 / 8 (100.00%) 4.000 8 / 8 (100.00%) 0.625 8 0 8 0.829 8 / 8 (100.00%) 8 0 0 0 3 0.416 5 / 8 (62.50%) 8 0 3 0 3 4731.38 8 8 0.00% 0 0
graph_native 2 lazy-graph-rag-wide lazy-graph-rag experimental 3 3.688 8 / 8 (100.00%) 0 3.625 8 / 8 (100.00%) 3.750 8 / 8 (100.00%) 0.375 8 1 6 0.843 8 / 8 (100.00%) 8 0 0 0 4 0.401 5 / 8 (62.50%) 8 0 3 0 4 5173.75 8 8 0.00% 0 0
graph_native 2 hybrid-rag-fast hybrid-rag canonical 5 3.625 8 / 8 (100.00%) 0 3.625 8 / 8 (100.00%) 3.625 8 / 8 (100.00%) 0.500 8 0 2 0.855 8 / 8 (100.00%) 8 0 0 0 6 0.382 6 / 8 (75.00%) 8 0 2 0 2 4380.50 8 8 0.00% 0 0
graph_native 2 lazy-graph-rag-fast lazy-graph-rag experimental 5 3.625 8 / 8 (100.00%) 0 3.375 8 / 8 (100.00%) 3.875 8 / 8 (100.00%) 0.500 8 1 7 0.833 8 / 8 (100.00%) 8 0 0 0 8 0.314 6 / 8 (75.00%) 8 0 2 0 1 3908.12 8 8 0.00% 0 0
graph_native 2 contextual-rag-high-recall contextual-rag canonical 7 3.375 8 / 8 (100.00%) 0 3.250 8 / 8 (100.00%) 3.500 8 / 8 (100.00%) 0.500 8 0 3 0.849 8 / 8 (100.00%) 8 0 0 0 1 0.531 6 / 8 (75.00%) 8 0 2 0 8 11707.50 8 8 0.00% 0 0
graph_native 2 graph-rag-wide graph-rag canonical 8 2.625 8 / 8 (100.00%) 0 2.500 8 / 8 (100.00%) 2.750 8 / 8 (100.00%) 0.500 8 1 10 0.816 8 / 8 (100.00%) 8 0 0 0 N/A N/A N/A 8 8 0 0 10 13365.50 8 8 0.00% 0 0
graph_native 2 graph-rag-rerank graph-rag canonical 9 2.438 8 / 8 (100.00%) 0 2.375 8 / 8 (100.00%) 2.500 8 / 8 (100.00%) 0.375 8 1 11 0.805 8 / 8 (100.00%) 8 0 0 0 N/A N/A N/A 8 8 0 0 12 14687.75 8 8 0.00% 0 0
graph_native 2 n8n-adaptive-rag-default n8n-adaptive-rag canonical 10 2.375 8 / 8 (100.00%) 0 2.250 8 / 8 (100.00%) 2.500 8 / 8 (100.00%) 0.250 8 0 12 0.740 8 / 8 (100.00%) 8 0 0 0 9 0.000 1 / 8 (12.50%) 8 0 7 0 5 5914.75 8 8 0.00% 0 0
graph_native 2 agentic-rag-deeper agentic-rag canonical 11 2.250 8 / 8 (100.00%) 0 2.250 8 / 8 (100.00%) 2.250 8 / 8 (100.00%) 0.250 8 0 4 0.849 8 / 8 (100.00%) 8 0 0 0 5 0.392 2 / 8 (25.00%) 8 0 6 0 11 13527.00 8 8 0.00% 0 0
graph_native 2 graph-rag-fast graph-rag canonical 12 2.062 8 / 8 (100.00%) 0 1.875 8 / 8 (100.00%) 2.250 8 / 8 (100.00%) 0.625 8 0 9 0.821 8 / 8 (100.00%) 8 0 0 0 N/A N/A N/A 8 8 0 0 9 11994.75 8 8 0.00% 0 0
cyber_threat_intel 7 hybrid-rag-fast hybrid-rag canonical 1 3.667 6 / 6 (100.00%) 0 3.333 6 / 6 (100.00%) 4.000 6 / 6 (100.00%) 1.000 6 2 5 0.844 6 / 6 (100.00%) 6 0 0 0 8 0.045 4 / 6 (66.67%) 6 0 2 0 1 6984.50 6 6 0.00% 0 0
cyber_threat_intel 7 contextual-rag-high-recall contextual-rag canonical 2 3.500 6 / 6 (100.00%) 0 3.167 6 / 6 (100.00%) 3.833 6 / 6 (100.00%) 0.667 6 0 10 0.811 6 / 6 (100.00%) 6 0 0 0 2 0.357 1 / 6 (16.67%) 6 0 5 0 12 40646.33 6 6 0.00% 0 0
cyber_threat_intel 7 hybrid-rag-high-recall hybrid-rag canonical 3 3.333 6 / 6 (100.00%) 0 3.000 6 / 6 (100.00%) 3.667 6 / 6 (100.00%) 0.667 6 1 1 0.890 6 / 6 (100.00%) 6 0 0 0 9 0.000 2 / 6 (33.33%) 6 0 4 0 11 39889.17 6 6 0.00% 0 0
cyber_threat_intel 7 lazy-graph-rag-fast lazy-graph-rag experimental 3 3.333 6 / 6 (100.00%) 0 2.833 6 / 6 (100.00%) 3.833 6 / 6 (100.00%) 1.333 6 1 7 0.827 6 / 6 (100.00%) 6 0 0 0 3 0.240 2 / 6 (33.33%) 6 0 4 0 2 7350.67 6 6 0.00% 0 0
cyber_threat_intel 7 lazy-graph-rag-balanced lazy-graph-rag experimental 5 3.000 6 / 6 (100.00%) 0 2.667 6 / 6 (100.00%) 3.333 6 / 6 (100.00%) 0.667 6 1 3 0.873 6 / 6 (100.00%) 6 0 0 0 6 0.121 3 / 6 (50.00%) 6 0 3 0 3 7955.67 6 6 0.00% 0 0
cyber_threat_intel 7 vanilla-rag-wide vanilla-rag canonical 5 3.000 6 / 6 (100.00%) 0 2.500 6 / 6 (100.00%) 3.500 6 / 6 (100.00%) 1.000 6 1 8 0.820 6 / 6 (100.00%) 6 0 0 0 7 0.059 3 / 6 (50.00%) 6 0 3 0 6 13370.50 6 6 0.00% 0 0
cyber_threat_intel 7 lazy-graph-rag-wide lazy-graph-rag experimental 7 2.917 6 / 6 (100.00%) 0 2.833 6 / 6 (100.00%) 3.000 6 / 6 (100.00%) 0.833 6 0 11 0.805 6 / 6 (100.00%) 6 0 0 0 5 0.208 2 / 6 (33.33%) 6 0 4 0 5 10781.33 6 6 0.00% 0 0
cyber_threat_intel 7 n8n-adaptive-rag-default n8n-adaptive-rag canonical 8 2.583 6 / 6 (100.00%) 0 2.000 6 / 6 (100.00%) 3.167 6 / 6 (100.00%) 1.167 6 0 2 0.877 6 / 6 (100.00%) 6 0 0 0 4 0.224 3 / 6 (50.00%) 6 0 3 0 4 10773.17 6 6 0.00% 0 0
cyber_threat_intel 7 agentic-rag-deeper agentic-rag canonical 9 2.417 6 / 6 (100.00%) 0 2.000 6 / 6 (100.00%) 2.833 6 / 6 (100.00%) 0.833 6 0 12 0.709 6 / 6 (100.00%) 6 0 0 0 1 0.531 2 / 6 (33.33%) 6 0 4 0 8 17243.00 6 6 0.00% 0 0
cyber_threat_intel 7 graph-rag-rerank graph-rag canonical 9 2.417 6 / 6 (100.00%) 0 2.167 6 / 6 (100.00%) 2.667 6 / 6 (100.00%) 0.500 6 0 9 0.820 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 10 31947.50 6 6 0.00% 0 0
cyber_threat_intel 7 graph-rag-wide graph-rag canonical 11 2.167 6 / 6 (100.00%) 0 1.833 6 / 6 (100.00%) 2.500 6 / 6 (100.00%) 0.667 6 0 4 0.864 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 9 26667.67 6 6 0.00% 0 0
cyber_threat_intel 7 graph-rag-fast graph-rag canonical 12 1.917 6 / 6 (100.00%) 0 1.667 6 / 6 (100.00%) 2.167 6 / 6 (100.00%) 0.500 6 0 6 0.841 6 / 6 (100.00%) 6 0 0 0 N/A N/A N/A 6 6 0 0 7 16581.83 6 6 0.00% 0 0